Course suggestion after ML & DL specialization

Hello Folks,
I completed the ML and DL specializations. I enjoyed both the courses and I am glad I followed through it. Now I want to continue my journey and I am wondering if it is better to take TensorFlow Advanced to get stronger with the TF coding or take NLP specialization to learn more concepts. Please share your suggestions and your experience. Thanks a lot.
Moh-

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Asking myself the same question, even if still have W2 to W4 of DL to complete.
At least for me, the answer is simple: both. I will start with NLP because I feel to be more in need of theoretical knowledge.
But afterward, TF will be by all means the next!
Happy learning :slight_smile:

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I agree: Both.

Hello @mnainar,

I believe to be great in anything you need to practice and until and unless you have built some projects and applied your learnings, doing specializations and getting certificates would be useless. My personal suggestion is to build some projects based on the concepts you’ve just learned in ML and DL specializations. Use TF to build them and see where you’re struggling and then if you feel you need to take TF Advanced certification, go ahead, or else move to the next topic, which is NLP. I hope this helps. All the best! :slight_smile:

-Abhi

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I want to practise more of what I learnt. So far, I have completed the ML specialization. But, I feel, my confidence is not so great when it comes to the practical element of my knowledge. Is there anything you can recommend in Coursera where I can find some good practical questions?

I don’t think there’s any specific course for practical questions on Coursera. What you can do is look in Kaggle, choose some learning or real datasets and start asking questions and building models to learn. The more you actually practice with actual data, the better you’ll get. Or you can take private coaching who can guide and mentor you for the same. Depends on your enthusiasm and also financial capacity. I hope this helps. All the best!
-Abhi :slight_smile:

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